Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models

被引:0
|
作者
Jianting Zhu
William Forsee
Rina Schumer
Mahesh Gautam
机构
[1] University of Wyoming,Department of Civil and Architectural Engineering
[2] Desert Research Institute,undefined
[3] Desert Research Institute,undefined
[4] California Department of Water Resources,undefined
来源
Climatic Change | 2013年 / 118卷
关键词
Return Period; Rainfall Intensity; Generalize Extreme Value; Bayesian Model Average; Generalize Extreme Value Distribution;
D O I
暂无
中图分类号
学科分类号
摘要
Changes in climate are expected to lead to changes in the characteristics extreme rainfall frequency and intensity. In this study, we propose an integrated approach to explore potential changes in intensity-duration-frequency (IDF) relationships. The approach incorporates uncertainties due to both the short simulation periods of regional climate models (RCMs) and the differences in IDF curves derived from multiple RCMs in the North American Regional Climate Change Assessment Program (NARCCAP). The approach combines the likelihood of individual RCMs according to the goodness of fit between the extreme rainfall intensities from the RCMs’ historic runs and those from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data set and Bayesian model averaging (BMA) to assess uncertainty in IDF predictions. We also partition overall uncertainties into within-model uncertainty and among-model uncertainty. Results illustrate that among-model uncertainty is the dominant source of the overall uncertainty in simulating extreme rainfall for multiple locations in the U.S., pointing to the difficulty of predicting future climate, especially extreme rainfall regimes. For all locations a more intense extreme rainfall occurs in future climate; however the rate of increase varies among locations.
引用
收藏
页码:469 / 485
页数:16
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